Diego Calderon
Impact in
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- Single-cell and spatial transcriptomics
- Genomics and Chromatin Dynamics
- CRISPR and Genetic Engineering
- Epigenetics and DNA Methylation
- RNA Research and Splicing
- Pluripotent Stem Cells Research
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- T-cell and B-cell Immunology
Papers in
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- Single-cell and spatial transcriptomics 4
- RNA and protein synthesis mechanisms 4
- Genomics and Chromatin Dynamics 3
- RNA Research and Splicing 3
- CRISPR and Genetic Engineering 3
- Epigenetics and DNA Methylation 2
- Advanced biosensing and bioanalysis techniques 1
- Protein Degradation and Inhibitors 1
- Oncology 1
- Co-authors
- Jonathan K. Pritchard (3 shared papers)David A. Knowles (2 shared papers)Beth Martin (5 shared papers)Jay Shendure (6 shared papers)David E. Golan (1 shared paper)Towfique Raj (1 shared paper)Anand Bhaskar (1 shared paper)Audrey Qiuyan Fu (1 shared paper)
- Journals
- Nature Genetics (2 papers)Nature Methods (1 paper)The American Journal of Human Genetics (1 paper)Science (1 paper)Nature Communications (1 paper)
- Partner nations
- United StatesGermanyIsrael
In The Last Decade
Diego Calderon
11 papers receiving 500 citations
Peers
Comparison fields: 5 of 60
- Molecular Biology 405
- Immunology 98
- Biophysics 26
- Genetics 104
- Cancer Research 55
Countries citing papers authored by Diego Calderon
This map shows the geographic impact of Diego Calderon's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Diego Calderon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Diego Calderon more than expected).
Fields of papers citing papers by Diego Calderon
This network shows the impact of papers produced by Diego Calderon. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Diego Calderon. The network helps show where Diego Calderon may publish in the future.
Co-authors
The 25 scholars most cited alongside Diego Calderon, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 152 | |
| 2 | 2022 | 85 | |
| 3 | 2017 | 78 | |
| 4 | 2017 | 74 | |
| 5 | 2022 | 45 | |
| 6 | 2024 | 35 | |
| 7 | 2024 | 14 | |
| 8 | 2024 | 13 | |
| 9 | 2025 | 3 | |
| 10 | Predicting Mitochondrial tRNA Modification | 2014 | 1 |
| 11 | 2011 | 1 |
About Diego Calderon
Diego Calderon is a scholar working on Molecular Biology, Oncology, Genetics, Immunology and Plant Science, having authored 11 papers that have together received 501 indexed citations. Recurring topics across this work include Single-cell and spatial transcriptomics (4 papers), RNA and protein synthesis mechanisms (4 papers), Genomics and Chromatin Dynamics (3 papers), RNA Research and Splicing (3 papers), CRISPR and Genetic Engineering (3 papers), Epigenetics and DNA Methylation (2 papers), Advanced biosensing and bioanalysis techniques (1 paper) and Protein Degradation and Inhibitors (1 paper). The work is most often cited by research in Molecular Biology (405 citations), Immunology (98 citations), Biophysics (26 citations), Genetics (104 citations) and Cancer Research (55 citations). Diego Calderon has collaborated with scholars based in United States, Germany and Israel. Frequent co-authors include Jonathan K. Pritchard, David A. Knowles, Beth Martin, Jay Shendure, David E. Golan, Towfique Raj, Anand Bhaskar, Audrey Qiuyan Fu, Cole Trapnell and Xingfan Huang. Their work appears in journals such as Nature Genetics, Nature Methods, The American Journal of Human Genetics, Science and Nature Communications.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.